SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

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Showing 271–280 of 4891 papers

TitleStatusHype
Efficient Neural Network Robustness Certification with General Activation FunctionsCode1
Efficient RAW Image Deblurring with Adaptive Frequency ModulationCode1
Efficient Long Sequence Modeling via State Space Augmented TransformerCode1
A machine learning-based viscoelastic-viscoplastic model for epoxy nanocomposites with moisture contentCode1
M3-Jepa: Multimodal Alignment via Multi-directional MoE based on the JEPA frameworkCode1
Efficient Multi-agent Reinforcement Learning by PlanningCode1
Efficient Real-time Path Planning with Self-evolving Particle Swarm Optimization in Dynamic ScenariosCode1
Efficient and Accurate Pneumonia Detection Using a Novel Multi-Scale Transformer ApproachCode1
A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with DroneCode1
Efficient and Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire DetectionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified